Virtual shared cache mechanism in a processing device

ABSTRACT

In accordance with embodiments disclosed herein, there is provided systems and methods for providing a virtual shared cache mechanism. A processing device includes a plurality of clusters allocated into a virtual private shared cache. Each of the clusters includes a plurality of cores and a plurality of cache slices co-located within the plurality of cores. The processing device also includes a virtual shared cache including the plurality of clusters such that the cache data in the plurality of cache slices is shared among the plurality of clusters.

TECHNICAL FIELD

The embodiments of the disclosure relate generally to processing devices, and, more specifically, relate to a virtual shared cache mechanism in a processing device.

BACKGROUND

Advances in semi-conductor processing and logic design have permitted an increase in the amount of logic that may be present on integrated circuit devices. As a result, computer system configurations have evolved from a single or multiple integrated circuits in a system to multiple cores, multiple hardware threads, and multiple logical processors present on individual integrated circuits. A processor or integrated circuit typically comprises a single physical processor die, where the processor die may include any number of cores, hardware threads, or logical processors.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure will be understood more fully from the detailed description given below and from the accompanying drawings of various embodiments of the disclosure. The drawings, however, should not be taken to limit the disclosure to the specific embodiments, but are for explanation and understanding only.

FIG. 1 is a block diagram of system architecture, according to one embodiment of the disclosure.

FIG. 2 illustrates details of the virtual shared cache of FIG. 1 according to one embodiment of the disclosure.

FIG. 3A is a flow diagram of a method for providing a virtual shared cache mechanism according to one embodiment of the disclosure.

FIG. 3B is a flow diagram of a method for providing a virtual shared cache mechanism according to another embodiment of the disclosure.

FIG. 4A is a block diagram illustrating an exemplary in order pipeline and an exemplary register renaming, out-of-order issue/execution pipeline in accordance with described embodiments.

FIG. 4B is a block diagram illustrating both an exemplary embodiment of an in-order architecture core and an exemplary register renaming, out-of-order issue/execution architecture core to be included in a processor in accordance with described embodiments.

FIG. 5 is a block diagram illustrating a processor according to one embodiment.

FIG. 6 illustrates a block diagram of a computer system according to one embodiment.

FIG. 7 is a block diagram of a system on chip (SoC) in accordance with an embodiment of the present disclosure.

FIG. 8 is a block diagram of an embodiment of a system on-chip (SOC) design.

FIG. 9 illustrates a block diagram of a computer system according to one embodiment.

FIG. 10 illustrates a block diagram of a computer system according to one embodiment.

FIG. 11 illustrates block diagram of an embodiment of tablet computing device, a smartphone, or other mobile device in which touchscreen interface connectors are used.

FIG. 12 illustrates a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.

DETAILED DESCRIPTION

Disclosed herein are embodiments for providing a virtual shared cache mechanism in chip multiprocessor (CMP) architectures.

Existing CMP architectures incorporate a shared and distributed cache structure. Cache slices of a cache may be co-located with cores into a cluster on a CMP. As such, multiple cache slices and cores are per cluster. All cores on a CMP usually have access to all cache slices within the cluster on the CMP. Also, a main memory storing data required by the cores is partitioned into a plurality of address regions and each cluster corresponds with an address region of the plurality of address regions. The data required by a core within a cluster is stored in the address region corresponding with the cluster.

Today the mechanism to bring data into a cache is through a pull-based mechanism. In the pull-based mechanism, for a given thread (sequence of programmed instructions) in the core, the core requests the data by pulling the data from the main memory into the cache co-located within the requesting core. Also, when data is to be evicted from the cache, the core evicts the cache data directly into the corresponding address region of the main memory. As such, each of the caches co-located within the core are called private caches as the cache data is only accessible to that core. However, the private cache is restricted to its core and not utilized by remaining caches in the shared cache structure. This results in capacity in many of the caches being wasted. Also, main memory is accessed every time the cache data is evicted from the local cache. Further, other clusters are snooped into every time the cache data needs to be accessed for a given thread. Snooping is performed to maintain cache coherency in symmetric multiprocessing environments.

Embodiments of the disclosure overcome the above problems by expanding the cache size beyond its own private cache. As such, a private cache in a cluster is available to other private caches in a different cluster perceived by a given thread. In one embodiment, a plurality of clusters form a virtual shared cache, which allows for each one of the plurality of clusters to apply shared cache allocation into each of the clusters. The virtual shared cache also functions to allow cache data push from one private cache in one cluster into another private cache that exist in the another portion of an another cluster. As such, the capacity of other private caches in different clusters is consumed for the given thread. Further, the virtual shared cache allows for quicker return of the cache data without snooping into other clusters for the cache data, which reduces the cache access latency.

In the following description, numerous specific details are set forth (for example, specific share logic implementations, virtual shared cache logic implementations, hardware/firmware partitioning details, logic partitioning/integration details, processor configurations, micro-architectural details, sequences of operations, types and interrelationships of system components, and the like). However, it is understood that embodiments of the invention may be practiced without these specific details. In other instances, well-known circuits, structures and techniques have not been shown in detail in order not to obscure the understanding of this description.

FIG. 1 illustrates a system architecture 100 that includes virtual shared cache according to an embodiment of the present disclosure. In an embodiment, the system architecture may be a system-on-a-chip hardware circuit block that may be implemented on a single die (a same substrate) and within a single semiconductor package. The processing unit may be a central processing unit (CPU) or a graphic processing unit (GPU).

Referring to FIG. 1, the processing unit may include a processor 102 coupled to a memory 160 via a memory manager 180. In one embodiment, the processor 102 incorporates a shared and distributed cache structure. In one embodiment, the processor 102 is logically separated into four clusters 110, 120, 130 and 140, called sub non-uniform access memory clusters (SNCs). Each SNC is a cluster of adjacent cores 112 and the co-located caches 114 grouped together. The memory manager 180 is configured to couple one or more caches 114 in the processor 102 to the memory 160.

Also shown is a virtual shared cache 150, which includes the SNC 110, SNC 120, SNC 130 and SNC 140. Specifically, the virtual shared cache 150 allows the processor 102 to apply dynamic shared cache allocation into each of the SNCs 110, 120, 130 and 140. The virtual shared cache 150 allows the cache capacity in each of the SNCs 110, 120, 130 and 140 to be shared among each other. Specifically, the virtual shared cache 150 allows data from the cache 114 of one of the SNCs to be moved to another of the SNCs.

In one embodiment, the virtual shared cache 150 also functions to allow the cache data to be pushed from one cache in one SNC into another cache that exist in the another portion of another SNC, which is different from the one SNC. Specifically, the core 112 pushes data from its cache 114 of one of the SNCs to the cache 114 of another of the SNCs. In order to create space for new data in its cache 114, the core 112 may push a pre-existing data in one of the SNCs to the another of the SNCs. In one example, a core 112 from the SNC 110 pushes cache data from the cache 114 within the core 112 to the cache 114 within the core 112 of the SNC 130.

In another embodiment, the virtual shared cache 150 also functions to allow the cache data to be searched in an SNC and in the virtual cache in parallel (i.e. at the same time). Specifically, the core 112 does not know whether the data is within in its own SNC or had been moved to another SNC. As such, the core 112 of one of the SNCs 110, 120, 130 and 140 searches for data both in its own SNC and within the virtual shared cache 150 at the same time. In one example, the core 112 from the SNC 110 searches for the cache data from the cache 114 within the SNC 110 and within the virtual shared cache 150 at the same time.

Although FIG. 1 illustrates a processor 102, which is separated into four SNCs with four cores each for ease of discussion, in other embodiments, the number of cores may vary from cluster to cluster and a processor may include any number of clusters.

FIG. 2 illustrates details of the virtual shared cache 150 of the processor 102 of FIG. 1 according to an embodiment. As discussed above, the clusters 110, 120, 130 and 140, called sub-NUMA clusters (SNCs). Each SNC is a cluster of adjacent cores and the co-located caches grouped together. In an embodiment, the caches may be part of a last level cache (LLC), i.e., the last cache in the memory hierarchy on a processor, such as a second or third level cache. In one embodiment, the memory 160 is soft partitioned into sub-NUMA address regions (SNARs) 210, 220, 230 and 240. As such, the SNAR 210 is associated with the SNC 110, the SNAR 220 is associated with the SNC 120, the SNAR 230 is associated with the SNC 130, and the SNAR 240 is associated with the SNC 130.

Each SNAR may be referenced into a contiguous portion of memory, which is mapped to the caches of the corresponding SNC. The contiguous portion of memory may be physically and/or logically contiguous. For example, the addresses of SNAR 210 may be evenly hashed to the cache of SNC 110, the addresses of SNAR 220 may be evenly hashed to the cache of SNC 120, the addresses of SNAR 230 may be evenly hashed to the cache of SNC 130, and the addresses of SNAR 240 may be evenly hashed to the cache of SNC 140. Cache accesses of a core in a particular SNC may be biased to the SNAR associated with that particular SNC. In other words, when a core from a particular SNC requires data, which may be stored in the SNAR associated with that particular SNC. For example, cache accesses of core 112 of SNC 110 may be biased to SNAR 210.

In an example embodiment, a thread executed on core 114 may require data 215. The first access of the data 215 may require retrieval of the data from a storage device such as a hard drive 270. Upon retrieval of the data 215 from the hard drive 270, the operating system may store it to the memory in SNAR 210 since the core 112 requesting the data 215 is located in the SNC 110 associated with the SNAR 210. Given that the addresses of SNAR 210 are hashed to the caches of SNC 110, the data 215 may be available in the cache(s) of SNC 110 for future requests. Partitioning a processor into SNCs and the memory into associated SNARs may decrease the cache latency since data required by a core will likely reside in a cache local to the core's SNC. In one embodiment, when one of the SNARs 210, 220, 230 and 240 is unable to store data, an OS may allocate data to another one of the SNARs 210, 220, 230 and 240 based on proximity (nearness in place) of one SNAR to another. The proximity is determined by the cache latency. In one example, the OS is unable to store data 215 in SNAR 210, for example, because SNAR 210 is full, the OS may allocate the data 215 to SNAR 220, since SNAR 220 is associated with SNC 220, which is the SNC closest to SNC 110.

Also shown is the virtual shared cache 150, which includes the SNC 110, SNC 120, SNC 130 and SNC 140. The virtual shared cache 150 functions to allow each of the SNC 110, SNC 120, SNC 130 and SNC 140 to be shared among each other.

Specifically, the virtual shared cache 150 allows the processor 102 to apply dynamic shared cache allocation into each of the SNCs 110, 120, 130 and 140.

In one embodiment, the virtual shared cache 150 also functions to allow cache data to be pushed from one cache into another cache that exist in the another portion of another SNC, which is different from the one SNC. As such, cache data is evicted from a private cache in one SNC to another private cache in another SNC, which is different from the one SNC. In one embodiment, a core within a SNC accesses new data (i.e. data which is currently not present in its own cluster), then it needs to create space in its own SNC to accommodate that new data. So, the core within the SNC chooses to evict the current data that is present in cache of the SNC. Accordingly, the core within the cluster decides to evict the data by pushing the current data into another cluster in the virtual shared cache.

As an example, core 112 from the SNC 110 needs to evict the cache data 215 from its cache 114, As such, in the example, the virtual shared cache 150 allows a core 112 from the SNC 110 to push the cache data 215 from the cache 114 within the core 112 to the cache 114 within the core 112 of the SNC 130. Accordingly, the total cache size is expanded beyond its local SNC.

In some embodiments, the cache data is pushed into another private cache based on a static mechanism. The static mechanism may determine which of one of the SNCs to push the cache data based on the address within an address range allocated to the cache in the SNC. As discussed above, the address in the address regions are allocated to the one or more caches in the SNC. So, the entire address space is statically divided in addresses between the different SNCs and each divided address is mapped to corresponding SNC. For example, when there are four SNCs 110, 120, 130 and 140, one-fourth of the addresses in the address space maps to each of the four SNCs 110, 120, 130 and 140. As such, the destination SNC to push the cache data is determined based on the address of the data that is evicted.

In one embodiment, the cache data is pushed into another private cache based on a dynamic mechanism. The dynamic mechanism may determine which of the SNCs to push the cache data into based on several run-time factors. One such factor is capacity of cache memory available in the one or more caches in the SNC. In some embodiments, the cache data is pushed to the SNC that has unused capacity to store the cache data. Another factor is operating status (e.g. idle, active etc.) of cores in the SNC. In some embodiments, the cache data is pushed to the SNC that has maximum number of idle cores. In other embodiments, the cache data is pushed to the SNC that has maximum number of active cores. Another factor is the usage of the caches by the active cores. In some embodiments, the cache data is pushed to the SNC with the active cores that are not using their corresponding caches. Another factor is the latency of the other SNCs. In one embodiment, the cache data may be pushed to the cache of the SNC closest to the core executing the thread. In one example, the SNC 130 is closest to the core 112 in the SNC 110 executing the thread. As such, the cache data in the cache 114 co-located to the core 112 in the SNC 110 is pushed to the cache 114 co-located to the core 112 in the SNC 130. Accordingly, the total cache size perceived by a given thread is dynamically expanded beyond its own local SNC.

In one embodiment, the cache data in a cache slice of one SNC may not be pushed to another cache slice in the another SNC even if it is closest to the core executing the thread. In such scenario, the another SNC may not have enough storage capacity in its cache slices to execute the thread and the another SNC may not wish to evict the cache data in its cache slices as the cache data may be needed to execute a specific thread, which may be useful.

In another embodiment, the virtual shared cache 150 also functions to allow for the cache data to be searched in one of the SNCs 110, 120, 130 and 140 and in the virtual shared cache including all other of the SNCs 110, 120, 130 and 140 in parallel (i.e. at the same time). For example, the core 112 in the SNC 110 may require the cache data 215 to execute a thread. Therefore, when the core 112 is searching for the cache data 215 in the cache 114 in its own SNC 110, it also searches for the cache data 215 in the cache 114 in the virtual shared cache 150 at the same time. In one embodiment, the core 112 in the SNC 110 sends the address of the cache 114 to the virtual shared cache 150. The virtual shared cache 150 determines which other SNC or SNCs 120, 130 or 140 may have caches 114 with the address. Accordingly, request(s) are then sent by the requesting core 112 of the SNC 110 to the other SNC or SNCs 120, 130 or 140 to look up the cache with the address. This search of the cache data in the SNC and the virtual shared cache at the same time reduces latency.

In one embodiment, the cache data 114 is retrieved at its own SNC 110. In another embodiment, the cache data 114 is retrieved by the core 112 from one of other SNCs 120, 130 and 140 from the virtual shared cache 150. Specifically, when the cache 114 with the address is present in the other SNC or SNCs, 120, 130 or 140, the requesting core 112 of the SNC 110 reads the data from this cache 114 and moves into the cache 114 in the SNC 110.

Although FIG. 2 illustrates a processor 102, which is separated into four SNCs with four cores each for ease of discussion, in other embodiments, the number of cores may vary from cluster to cluster and a processor may include any number of clusters. Similarly, there does not have to be a one-to-one correspondence between the SNARs and the SNCs. In an embodiment, one or more SNCs may correspond to a single SNAR. In an embodiment, a single SNC may correspond to one or more SNARs.

FIG. 3A is a flow diagram of a method for providing virtual shared cache mechanism in a processing device according to an embodiment of the disclosure. Method 300 may be performed by processing logic that may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (such as instructions run on a processing device, a general purpose computer system, or a dedicated machine), firmware, or a combination thereof. In one embodiment, method 300 may be performed, in part, by processor 102 described above with respect to FIG. 1.

For simplicity of explanation, the method 300 is depicted and described as a series of acts. However, acts in accordance with this disclosure can occur in various orders and/or concurrently and with other acts not presented and described herein. Furthermore, not all illustrated acts may be performed to implement the method 300 in accordance with the disclosed subject matter. In addition, those skilled in the art will understand and appreciate that the method 300 could alternatively be represented as a series of interrelated states via a state diagram or events.

Referring to FIG. 3A, at block 302 the processing logic allocates a plurality of clusters into a virtual shared cache. In one embodiment, each of the plurality of clusters includes a plurality of cores of a processor and a plurality of cache slices co-located within the plurality of cores. As such, the virtual shared cache allows for each of the plurality of clusters to be shared among each other. At block 304, it is determined that a cluster among the plurality of clusters is to evict the cache data. As discussed above, when a core within a cluster accesses new data (i.e. data which is currently not present in its own cluster), then it needs to create space in its own cluster to accommodate for that new data. Therefore, the core within the cluster chooses to evict the current data that is present in cache of the cluster. Accordingly, the core within the cluster pushes the current data into another cluster in the virtual shared cache.

At block 306, it is determined as to which cluster among the plurality of clusters in the virtual shared cache to push the cache data. In one embodiment, the cache data is stored in one of the cache slices co-located within the core of a one cluster among the plurality of clusters in the virtual shared cache. In one embodiment, the cluster to push the cache data into is determined based on a static mechanism. As discussed above, the static mechanism may determine which cluster in the virtual shared cache to push the cache data based on the address within an address range allocated to the cache in the cluster. As discussed above, the address in the address regions are allocated to the one or more caches in the cluster. Therefore, the entire address space is statically divided in addresses between the different clusters and each divided address is mapped to corresponding cluster. For example, when there are four clusters, one-fourth of the addresses in the address space maps to each of the four clusters. As such, the destination cluster to push the cache data is determined based on the address of the cache data that is evicted.

In another embodiment, the cluster to push the cache data into is determined based on a dynamic mechanism. Also as discussed above, the dynamic mechanism may determine which cluster in the virtual shared cache to push the cache data is based on several factors.

Also, as discussed above, one such factor is capacity of cache memory available in the one or more caches in the cluster. In some embodiments, the cache data is pushed to the cluster that has unused capacity to store the cache data. Also, as discussed above, another factor is operating status (e.g. idle, active etc.) of cores in the cluster. In some embodiments, the cache data is pushed to the cluster that has maximum number of idle cores. In other embodiments, the cache data is pushed to the cluster that has maximum number of active cores. Also, as discussed above, another factor is the usage of the caches by the active cores. In some embodiments, the cache data is pushed to the cluster with the active cores that are not using their corresponding caches. Also, as discussed above, another factor is the latency of the other clusters. In one embodiment, the cache data may be pushed to the cache of the cluster closest to the core executing the thread. Accordingly, the total cache size perceived by a given thread is dynamically expanded beyond its own local cluster.

In one embodiment, as discussed above, the cache data in a cache slice of one cluster may not be pushed to another cache slice in the another cluster even if it is closest to the core executing the thread. In such scenario, the another cluster may not have enough storage capacity in its cache slices to execute the thread and the another cluster may not wish to evict the cache data in its cache slices as the cache data may be needed to execute a specific thread, which may be useful.

At block 308, the cache data is pushed into the cluster in the virtual shared cache. In one embodiment, cache data stored in one of the cache slices co-located within the core of the one cluster in the private cache is pushed into another cache slice co-located within the core of an another cluster in the private cache.

FIG. 3B is a flow diagram of a method for providing virtual shared cache mechanism according to an embodiment of the disclosure. Method 320 may be performed by processing logic that may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (such as instructions run on a processing device, a general purpose computer system, or a dedicated machine), firmware, or a combination thereof. In one embodiment, method 320 may be performed, in part, by processor 102 described above with respect to FIG. 1.

For simplicity of explanation, the method 320 is depicted and described as a series of acts. However, acts in accordance with this disclosure can occur in various orders and/or concurrently and with other acts not presented and described herein. Furthermore, not all illustrated acts may be performed to implement the method 320 in accordance with the disclosed subject matter. In addition, those skilled in the art will understand and appreciate that the method 320 could alternatively be represented as a series of interrelated states via a state diagram or events.

Referring to FIG. 3B, at block 322 the processing logic allocates a plurality of clusters into a virtual shared cache. In one embodiment, each of the plurality of clusters includes a plurality of cores of a processor and a plurality of cache slices co-located within the plurality of cores. As such, the virtual shared cache allows for each of the clusters to be shared among each other. At block 324, a core in a cluster among the plurality of clusters requires cache data to execute a thread. At block 326, the cache data is searched in the cluster itself and in the virtual shared cache in parallel (i.e. at the same time). In one embodiment, a requesting core in the cluster searching for the data sends the address of the data to the virtual shared cache. The virtual shared cache determines which other cluster(s) may have caches with the address. Accordingly, request(s) are then sent by the requesting core of the cluster to the other cluster(s) to look up the cache with the address. This search of the cache data in the cluster(s) and the virtual shared cache at the same time reduces latency.

At block 328, the cache data is retrieved from the cluster or the virtual shared cache. In one embodiment, the cache data is retrieved at its own cluster. In another embodiment, the cache data is retrieved by the core from other cluster(s) from the virtual shared cache 150. Specifically, when the cache with the address is present in the other cluster(s), the requesting core of the cluster reads the data from this cache and moves into the cache in the cluster itself. At block 330, the core in the cluster executes the thread using the retrieved cache data.

FIG. 4A is a block diagram illustrating an in-order pipeline and a register re-naming stage, out-of-order issue/execution pipeline of a processor monitoring performance of a processing device to manage non-precise events according to at least one embodiment of the invention. FIG. 4B is a block diagram illustrating an in-order architecture core and a register renaming logic, out-of-order issue/execution logic to be included in a processor according to at least one embodiment of the invention. The solid lined boxes in FIG. 4A illustrate the in-order pipeline, while the dashed lined boxes illustrates the register renaming, out-of-order issue/execution pipeline. Similarly, the solid lined boxes in FIG. 4B illustrate the in-order architecture logic, while the dashed lined boxes illustrates the register renaming logic and out-of-order issue/execution logic.

In FIG. 4A, a processor pipeline 400 includes a fetch stage 402, a length decode stage 404, a decode stage 406, an allocation stage 408, a renaming stage 410, a scheduling (also known as a dispatch or issue) stage 412, a register read/memory read stage 414, an execute stage 416, a write back/memory write stage 418, an exception handling stage 422, and a commit stage 424. In some embodiments, the stages are provided in a different order and different stages may be considered in-order and out-of-order.

In FIG. 4B, arrows denote a coupling between two or more units and the direction of the arrow indicates a direction of data flow between those units. FIG. 4B shows processor core 490 including a front end unit 430 coupled to an execution engine unit 450, and both are coupled to a memory unit 70.

The core 490 may be a reduced instruction set computing (RISC) core, a complex instruction set computing (CISC) core, a very long instruction word (VLIW) core, or a hybrid or alternative core type. As yet another option, the core 490 may be a special-purpose core, such as, for example, a network or communication core, compression engine, graphics core, or the like.

The front end unit 430 includes a branch prediction unit 432 coupled to an instruction cache unit 434, which is coupled to an instruction translation lookaside buffer (TLB) 436, which is coupled to an instruction fetch unit 438, which is coupled to a decode unit 440. The decode unit or decoder may decode instructions, and generate as an output one or more micro-operations, micro-code entry points, microinstructions, other instructions, or other control signals, which are decoded from, or which otherwise reflect, or are derived from, the original instructions. The decoder may be implemented using various different mechanisms. Examples of suitable mechanisms include, but are not limited to, look-up tables, hardware implementations, programmable logic arrays (PLAs), microcode read only memories (ROMs), etc. The instruction cache unit 434 is further coupled to a level 2 (L2) cache unit 476 in the memory unit 470. The decode unit 440 is coupled to a rename/allocator unit 452 in the execution engine unit 450.

The execution engine unit 450 includes the rename/allocator unit 452 coupled to a retirement unit 454 and a set of one or more scheduler unit(s) 456. The retirement unit 454 may include a virtual shared cache mechanism module according to embodiments of the invention. The scheduler unit(s) 456 represents any number of different schedulers, including reservations stations, central instruction window, etc. The scheduler unit(s) 456 is coupled to the physical register file(s) unit(s) 458. Each of the physical register file(s) units 458 represents one or more physical register files, different ones of which store one or more different data types, such as scalar integer, scalar floating point, packed integer, packed floating point, vector integer, vector floating point, etc., status (e.g., an instruction pointer that is the address of the next instruction to be executed), etc. The physical register file(s) unit(s) 458 is overlapped by the retirement unit 454 to illustrate various ways in which register renaming and out-of-order execution may be implemented (e.g., using a reorder buffer(s) and a retirement register file(s), using a future file(s), a history buffer(s), and a retirement register file(s); using a register maps and a pool of registers; etc.).

Generally, the architectural registers are visible from the outside of the processor or from a programmer's perspective. The registers are not limited to any known particular type of circuit. Various different types of registers are suitable as long as they are capable of storing and providing data as described herein. Examples of suitable registers include, but are not limited to, dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc. The retirement unit 454 and the physical register file(s) unit(s) 458 are coupled to the execution cluster(s) 460. The execution cluster(s) 460 includes a set of one or more execution units 462 and a set of one or more memory access units 464. The execution units 462 may perform various operations (e.g., shifts, addition, subtraction, multiplication) and on various types of data (e.g., scalar floating point, packed integer, packed floating point, vector integer, vector floating point).

While some embodiments may include a number of execution units dedicated to specific functions or sets of functions, other embodiments may include one execution unit or multiple execution units that all perform all functions. The scheduler unit(s) 456, physical register file(s) unit(s) 458, and execution cluster(s) 460 are shown as being possibly plural because certain embodiments create separate pipelines for certain types of data/operations (e.g., a scalar integer pipeline, a scalar floating point/packed integer/packed floating point/vector integer/vector floating point pipeline, and/or a memory access pipeline that each have their own scheduler unit, physical register file(s) unit, and/or execution cluster—and in the case of a separate memory access pipeline, certain embodiments are implemented in which the execution cluster of this pipeline has the memory access unit(s) 464). It should also be understood that where separate pipelines are used, one or more of these pipelines may be out-of-order issue/execution and the rest in-order.

The set of memory access units 464 is coupled to the memory unit 470, which includes a data TLB unit 472 coupled to a data cache unit 474 coupled to a level 2 (L2) cache unit 476. In one exemplary embodiment, the memory access units 464 may include a load unit, a store address unit, and a store data unit, each of which is coupled to the data TLB unit 472 in the memory unit 470. The L2 cache unit 476 is coupled to one or more other levels of cache and eventually to a main memory.

By way of example, the exemplary register renaming, out-of-order issue/execution core architecture may implement the pipeline 400 as follows: 1) the instruction fetch 38 performs the fetch and length decoding stages 402 and 404; 2) the decode unit 440 performs the decode stage 406; 3) the rename/allocator unit 452 performs the allocation stage 408 and renaming stage 410; 4) the scheduler unit(s) 456 performs the schedule stage 412; 5) the physical register file(s) unit(s) 458 and the memory unit 470 perform the register read/memory read stage 414; the execution cluster 460 perform the execute stage 416; 6) the memory unit 470 and the physical register file(s) unit(s) 458 perform the write back/memory write stage 418; 7) various units may be involved in the exception handling stage 422; and 8) the retirement unit 454 and the physical register file(s) unit(s) 458 perform the commit stage 424.

The core 490 may support one or more instructions sets (e.g., the x86 instruction set (with some extensions that have been added with newer versions); the MIPS instruction set of MIPS Technologies of Sunnyvale, Calif.; the ARM instruction set (with additional extensions such as NEON) of ARM Holdings of Sunnyvale, Calif.).

It should be understood that the core may support multithreading (executing two or more parallel sets of operations or threads), and may do so in a variety of ways including time sliced multithreading, simultaneous multithreading (where a single physical core provides a logical core for each of the threads that physical core is simultaneously multithreading), or a combination thereof (e.g., time sliced fetching and decoding and simultaneous multithreading thereafter such as in the Intel® Hyperthreading technology).

While register renaming is described in the context of out-of-order execution, it should be understood that register renaming may be used in-order architecture. While the illustrated embodiment of the processor also includes a separate instruction and data cache units 434/474 and a shared L2 cache unit 476, alternative embodiments may have a single internal cache for both instructions and data, such as, for example, a Level 1 (L1) internal cache, or multiple levels of internal cache. In some embodiments, the system may include a combination of an internal cache and an external cache that is external to the core and/or the processor. Alternatively, all of the cache may be external to the core and/or the processor.

FIG. 5 is a block diagram illustrating a micro-architecture for a processor 500 that includes logic circuits to perform instructions in accordance with one embodiment of the invention. In one embodiment, processor 500 monitors performance of a processing device to manage non-precise events. In some embodiments, an instruction in accordance with one embodiment can be implemented to operate on data elements having sizes of byte, word, doubleword, quadword, etc., as well as datatypes, such as single and double precision integer and floating point datatypes. In one embodiment the in-order front end 501 is the part of the processor 500 that fetches instructions to be executed and prepares them to be used later in the processor pipeline. The front end 501 may include several units. In one embodiment, the instruction prefetcher 526 fetches instructions from memory and feeds them to an instruction decoder 528, which in turn decodes or interprets them. For example, in one embodiment, the decoder decodes a received instruction into one or more operations called “micro-instructions” or “micro-operations” (also called micro op or uops) that the machine can execute.

In other embodiments, the decoder parses the instruction into an opcode and corresponding data and control fields that are used by the micro-architecture to perform operations in accordance with one embodiment. In one embodiment, the trace cache 530 takes decoded uops and assembles them into program ordered sequences or traces in the uop queue 534 for execution. When the trace cache 530 encounters a complex instruction, the microcode ROM 532 provides the uops needed to complete the operation.

Some instructions are converted into a single micro-op, whereas others use several micro-ops to complete the full operation. In one embodiment, if more than four micro-ops are needed to complete an instruction, the decoder 528 accesses the microcode ROM 532 to do the instruction. For one embodiment, an instruction can be decoded into a small number of micro ops for processing at the instruction decoder 528. In another embodiment, an instruction can be stored within the microcode ROM 532 should a number of micro-ops be needed to accomplish the operation. The trace cache 530 refers to an entry point programmable logic array (PLA) to determine a correct micro-instruction pointer for reading the micro-code sequences to complete one or more instructions in accordance with one embodiment from the micro-code ROM 532. After the microcode ROM 532 finishes sequencing micro-ops for an instruction, the front end 501 of the machine resumes fetching micro-ops from the trace cache 530.

The out-of-order execution engine 503 is where the instructions are prepared for execution. The out-of-order execution logic has a number of buffers to smooth out and re-order the flow of instructions to optimize performance as they go down the pipeline and get scheduled for execution. The allocator logic allocates the machine buffers and resources that each uop needs in order to execute. The register renaming logic renames logic registers onto entries in a register file. The allocator also allocates an entry for each uop in one of the two uop queues, one for memory operations and one for non-memory operations, in front of the instruction schedulers: memory scheduler, fast scheduler 502, slow/general floating point scheduler 504, and simple floating point scheduler 506. The uop schedulers 502, 504, 506 determine when a uop is ready to execute based on the readiness of their dependent input register operand sources and the availability of the execution resources the uops use to complete their operation. The fast scheduler 502 of one embodiment can schedule on each half of the main clock cycle while the other schedulers can schedule once per main processor clock cycle. The schedulers arbitrate for the dispatch ports to schedule uops for execution.

Register files 508, 510 sit between the schedulers 502, 504, 506, and the execution units 512, 514, 516, 518, 520, 522, 524 in the execution block 511. There is a separate register file for integer and floating point operations, respectively. Each register file 508, 510, of one embodiment also includes a bypass network that can bypass or forward just completed results that have not yet been written into the register file to new dependent uops. The integer register file 508 and the floating point register file 510 are also capable of communicating data with the other. For one embodiment, the integer register file 508 is split into two separate register files, one register file for the low order 32 bits of data and a second register file for the high order 32 bits of data. The floating point register file 510 of one embodiment has 128 bit wide entries because floating point instructions typically have operands from 66 to 128 bits in width.

The execution block 511 contains the execution units 512, 514, 516, 518, 520, 522, 524, where the instructions are actually executed. This section includes the register files 508, 510, that store the integer and floating point data operand values that the micro-instructions use to execute. The processor 500 of one embodiment is comprised of a number of execution units: address generation unit (AGU) 512, AGU 514, fast ALU 516, fast ALU 518, slow ALU 520, floating point ALU 522, floating point move unit 524. For one embodiment, the floating point execution blocks 522, 524, execute floating point, MMX, SIMD, and SSE, or other operations. The floating point ALU 522 of one embodiment includes a 64 bit by 54 bit floating point divider to execute divide, square root, and remainder micro-ops. For embodiments of the invention, instructions involving a floating point value may be handled with the floating point hardware.

In one embodiment, the ALU operations go to the high-speed ALU execution units 516, 518. The fast ALUs 516, 518, of one embodiment can execute fast operations with an effective latency of half a clock cycle. For one embodiment, most complex integer operations go to the slow ALU 520 as the slow ALU 520 includes integer execution hardware for long latency type of operations, such as a multiplier, shifts, flag logic, and branch processing. Memory load/store operations are executed by the AGUs 512, 514. For one embodiment, the integer ALUs 516, 518, 520 are described in the context of performing integer operations on 64 bit data operands. In alternative embodiments, the ALUs 516, 518, 520 can be implemented to support a variety of data bits including 16, 32, 128, 256, etc. Similarly, the floating point units 522, 524 can be implemented to support a range of operands having bits of various widths. For one embodiment, the floating point units 522, 524 can operate on 128 bits wide packed data operands in conjunction with SIMD and multimedia instructions.

In one embodiment, the uops schedulers 502, 504, 506 dispatch dependent operations before the parent load has finished executing. As uops are speculatively scheduled and executed in processor 500, the processor 500 also includes logic to handle memory misses. If a data load misses in the data cache, there can be dependent operations in flight in the pipeline that have left the scheduler with temporarily incorrect data. A replay mechanism tracks and re-executes instructions that use incorrect data. The dependent operations should be replayed and the independent ones are allowed to complete. The schedulers and replay mechanism of one embodiment of a processor are also designed to catch instruction sequences for text string comparison operations.

The processor 500 may include a retirement unit 554 coupled to the execution block 511. The retirement unit 554 may include a virtual share cache mechanism module according to embodiments of the invention.

The term “registers” may refer to the on-board processor storage locations that are used as part of instructions to identify operands. In other words, registers may be those that are usable from the outside of the processor (from a programmer's perspective). However, the registers of an embodiment should not be limited in meaning to a particular type of circuit. Rather, a register of an embodiment is capable of storing and providing data, and performing the functions described herein. The registers described herein can be implemented by circuitry within a processor using any number of different techniques, such as dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc. In one embodiment, integer registers store thirty-two bit integer data.

A register file of one embodiment also contains eight multimedia SIMD registers for packed data. For the discussions below, the registers are understood to be data registers designed to hold packed data, such as 64 bits wide MMX registers (also referred to as ‘mm’ registers in some instances) in microprocessors enabled with the MMX™ technology from Intel Corporation of Santa Clara, Calif. These MMX registers, available in both integer and floating point forms, can operate with packed data elements that accompany SIMD and SSE instructions. Similarly, 128 bits wide XMM registers relating to SSE2, SSE3, SSE4, or beyond (referred to generically as “SSEx”) technology can also be used to hold such packed data operands. In one embodiment, in storing packed data and integer data, the registers do not differentiate between the two data types. In one embodiment, integer and floating point are contained in either the same register file or different register files. Furthermore, in one embodiment, floating point and integer data may be stored in different registers or the same registers.

Referring now to FIG. 6, shown is a block diagram of a system 600 in accordance with one embodiment of the invention. The system 600 may include one or more processors 610, 615, which are coupled to graphics memory controller hub (GMCH) 620. The optional nature of additional processors 615 is denoted in FIG. 6 with broken lines. In one embodiment, a processor 610, 615 monitors performance of a processing device to manage non-precise events.

Each processor 610, 615 may be some version of the circuit, integrated circuit, processor, and/or silicon integrated circuit as described above. However, it should be noted that it is unlikely that integrated graphics logic and integrated memory control units would exist in the processors 610, 615. FIG. 6 illustrates that the GMCH 620 may be coupled to a memory 640 that may be, for example, a dynamic random access memory (DRAM). The DRAM may, for at least one embodiment, be associated with a non-volatile cache.

The GMCH 620 may be a chipset, or a portion of a chipset. The GMCH 620 may communicate with the processor(s) 610, 615 and control interaction between the processor(s) 610, 615 and memory 640. The GMCH 620 may also act as an accelerated bus interface between the processor(s) 610, 615 and other elements of the system 600. For at least one embodiment, the GMCH 620 communicates with the processor(s) 610, 615 via a multi-drop bus, such as a frontside bus (FSB) 695.

Furthermore, GMCH 620 is coupled to a display 645 (such as a flat panel or touchscreen display). GMCH 620 may include an integrated graphics accelerator. GMCH 620 is further coupled to an input/output (I/O) controller hub (ICH) 650, which may be used to couple various peripheral devices to system 600. Shown for example in the embodiment of FIG. 6 is an external graphics device 660, which may be a discrete graphics device coupled to ICH 650, along with another peripheral device 670.

Alternatively, additional or different processors may also be present in the system 600. For example, additional processor(s) 615 may include additional processors(s) that are the same as processor 610, additional processor(s) that are heterogeneous or asymmetric to processor 610, accelerators (such as, e.g., graphics accelerators or digital signal processing (DSP) units), field programmable gate arrays, or any other processor. There can be a variety of differences between the processor(s) 610, 615 in terms of a spectrum of metrics of merit including architectural, micro-architectural thermal, power consumption characteristics, and the like. These differences may effectively manifest themselves as asymmetry and heterogeneity amongst the processors 610, 615. For at least one embodiment, the various processors 610, 615 may reside in the same die package.

Embodiments may be implemented in many different system types. FIG. 7 is a block diagram of a SoC 700 in accordance with an embodiment of the present disclosure. Dashed lined boxes are optional features on more advanced SoCs. In FIG. 7, an interconnect unit(s) 712 is coupled to: an application processor 720 which includes a set of one or more cores 702A-N and shared cache unit(s) 706; a system agent unit 710; a bus controller unit(s) 716; an integrated memory controller unit(s) 714; a set or one or more media processors 718 which may include integrated graphics logic 708, an image processor 724 for providing still and/or video camera functionality, an audio processor 726 for providing hardware audio acceleration, and a video processor 728 for providing video encode/decode acceleration; an static random access memory (SRAM) unit 730; a direct memory access (DMA) unit 732; and a display unit 740 for coupling to one or more external displays. In one embodiment, a memory module may be included in the integrated memory controller unit(s) 714. In another embodiment, the memory module may be included in one or more other components of the SoC 700 that may be used to access and/or control a memory. The application processor 720 may include a conditional branch, indirect branch and event execution logics as described in embodiments herein.

The memory hierarchy includes one or more levels of cache within the cores, a set or one or more shared cache units 706, and external memory (not shown) coupled to the set of integrated memory controller units 714. The set of shared cache units 706 may include one or more mid-level caches, such as level 2 (L2), level 3 (L3), level 4 (L4), or other levels of cache, a last level cache (LLC), and/or combinations thereof.

In some embodiments, one or more of the cores 702A-N are capable of multi-threading.

The system agent 710 includes those components coordinating and operating cores 702A-N. The system agent unit 710 may include for example a power control unit (PCU) and a display unit. The PCU may be or include logic and components needed for regulating the power state of the cores 702A-N and the integrated graphics logic 708. The display unit is for driving one or more externally connected displays.

The cores 702A-N may be homogenous or heterogeneous in terms of architecture and/or instruction set. For example, some of the cores 702A-N may be in order while others are out-of-order. As another example, two or more of the cores 702A-N may be capable of execution the same instruction set, while others may be capable of executing only a subset of that instruction set or a different instruction set.

The application processor 720 may be a general-purpose processor, such as a Core™ i3, i5, i7, 2 Duo and Quad, Xeon™, Itanium™, Atom™, XScale™ or StrongARM™ processor, which are available from Intel™ Corporation, of Santa Clara, Calif. Alternatively, the application processor 720 may be from another company, such as ARM Holdings™, Ltd, MIPS™, etc. The application processor 720 may be a special-purpose processor, such as, for example, a network or communication processor, compression engine, graphics processor, co-processor, embedded processor, or the like. The application processor 720 may be implemented on one or more chips. The application processor 720 may be a part of and/or may be implemented on one or more substrates using any of a number of process technologies, such as, for example, BiCMOS, CMOS, or NMOS.

FIG. 8 is a block diagram of an embodiment of a system on-chip (SoC) design in accordance with the present disclosure. As a specific illustrative example, SoC 800 is included in user equipment (UE). In one embodiment, UE refers to any device to be used by an end-user to communicate, such as a hand-held phone, smartphone, tablet, ultra-thin notebook, notebook with broadband adapter, or any other similar communication device. Often a UE connects to a base station or node, which potentially corresponds in nature to a mobile station (MS) in a GSM network.

Here, SOC 800 includes 2 cores—806 and 807. Cores 806 and 807 may conform to an Instruction Set Architecture, such as an Intel® Architecture Core™-based processor, an Advanced Micro Devices, Inc. (AMD) processor, a MIPS-based processor, an ARM-based processor design, or a customer thereof, as well as their licensees or adopters. Cores 806 and 807 are coupled to cache control 808 that is associated with bus interface unit 808 and L2 cache 810 to communicate with other parts of system 800. Interconnect 810 includes an on-chip interconnect, such as an IOSF, AMBA, or other interconnect discussed above, which potentially implements one or more aspects of the described disclosure. In one embodiment, a conditional branch, indirect branch and event execution logics may be included in cores 806, 807.

Interconnect 810 provides communication channels to the other components, such as a Subscriber Identity Module (SIM) 830 to interface with a SIM card, a boot ROM 835 to hold boot code for execution by cores 806 and 807 to initialize and boot SoC 800, a SDRAM controller 840 to interface with external memory (e.g. DRAM 860), a flash controller 845 to interface with non-volatile memory (e.g. Flash 865), a peripheral control 850 (e.g. Serial Peripheral Interface) to interface with peripherals, video codecs 820 and Video interface 825 to display and receive input (e.g. touch enabled input), GPU 815 to perform graphics related computations, etc. Any of these interfaces may incorporate aspects of the disclosure described herein. In addition, the system 800 illustrates peripherals for communication, such as a Bluetooth module 870, 3G modem 875, GPS 880, and Wi-Fi 885.

Referring now to FIG. 9, shown is a block diagram of a system 900 in accordance with an embodiment of the invention. As shown in FIG. 9, multiprocessor system 900 is a point-to-point interconnect system, and includes a first processor 970 and a second processor 980 coupled via a point-to-point interconnect 950. Each of processors 970 and 980 may be some version of the processors of the computing systems as described herein. In one embodiment, processors 970, 980 monitoring performance of a processing device to manage non-precise events to monitor performance of a processing device to manage non-precise events.

While shown with two processors 970, 980, it is to be understood that the scope of the disclosure is not so limited. In other embodiments, one or more additional processors may be present in a given processor.

Processors 970 and 980 are shown including integrated memory controller units 972 and 982, respectively. Processor 970 also includes as part of its bus controller units point-to-point (P-P) interfaces 976 and 978; similarly, second processor 980 includes P-P interfaces 986 and 988. Processors 970, 980 may exchange information via a point-to-point (P-P) interface 950 using P-P interface circuits 978, 988. As shown in FIG. 9, IMCs 972 and 982 couple the processors to respective memories, namely a memory 932 and a memory 934, which may be portions of main memory locally attached to the respective processors.

Processors 970 and 980 may each exchange information with a chipset 990 via individual P-P interfaces 952, 954 using point to point interface circuits 976, 994, 986, 998. Chipset 990 may also exchange information with a high-performance graphics circuit 938 via a high-performance graphics interface 939.

A shared cache (not shown) may be included in either processor or outside of both processors, yet connected with the processors via P-P interconnect, such that either or both processors' local cache information may be stored in the shared cache if a processor is placed into a low power mode.

Chipset 990 may be coupled to a first bus 916 via an interface 996. In one embodiment, first bus 916 may be a Peripheral Component Interconnect (PCI) bus, or a bus such as a PCI Express bus or another third generation I/O interconnect bus, although the scope of the disclosure is not so limited.

As shown in FIG. 9, various I/O devices 914 may be coupled to first bus 916, along with a bus bridge 918, which couples first bus 916 to a second bus 920. In one embodiment, second bus 920 may be a low pin count (LPC) bus. Various devices may be coupled to second bus 920 including, for example, a keyboard and/or mouse 922, communication devices 927 and a storage unit 928 such as a disk drive or other mass storage device which may include instructions/code and data 930, in one embodiment. Further, an audio I/O 924 may be coupled to second bus 920. Note that other architectures are possible. For example, instead of the point-to-point architecture of FIG. 9, a system may implement a multi-drop bus or other such architecture.

Referring now to FIG. 10, shown is a block diagram of a system 1000 in accordance with an embodiment of the invention. FIG. 10 illustrates processors 1070, 1080. In one embodiment, processors 1070, 1080 monitor performance of a processing device to manage non-precise events. Furthermore, processors 1070, 1080 may include integrated memory and I/O control logic (“CL”) 1072 and 1082, respectively and intercommunicate with each other via point-to-point interconnect 1050 between point-to-point (P-P) interfaces 1078 and 1088 respectively. Processors 1070, 1080 each communicate with chipset 1090 via point-to-point interconnect 1052 and 1054 through the respective P-P interfaces 1076 to 1094 and 1086 to 1098 as shown. For at least one embodiment, the CL 1072, 1082 may include integrated memory controller units. CLs 1072, 1082 may include I/O control logic. As depicted, memories 1032, 1034 coupled to CLs 1072, 1082 and I/O devices 1014 are also coupled to the control logic 1072, 1082. Legacy I/O devices 1015 are coupled to the chipset 1090 via interface 1096.

FIG. 11 illustrates a block diagram 1100 of an embodiment of tablet computing device, a smartphone, or other mobile device in which touchscreen interface connectors may be used. Processor 1110 may monitor performance of a processing device to manage non-precise events. In addition, processor 1110 performs the primary processing operations. Audio subsystem 1120 represents hardware (e.g., audio hardware and audio circuits) and software (e.g., drivers, codecs) components associated with providing audio functions to the computing device. In one embodiment, a user interacts with the tablet computing device or smartphone by providing audio commands that are received and processed by processor 1110.

Display subsystem 1132 represents hardware (e.g., display devices) and software (e.g., drivers) components that provide a visual and/or tactile display for a user to interact with the tablet computing device or smartphone. Display subsystem 1130 includes display interface 1132, which includes the particular screen or hardware device used to provide a display to a user. In one embodiment, display subsystem 1130 includes a touchscreen device that provides both output and input to a user.

I/O controller 1140 represents hardware devices and software components related to interaction with a user. I/O controller 1140 can operate to manage hardware that is part of audio subsystem 1120 and/or display subsystem 1130. Additionally, I/O controller 1140 illustrates a connection point for additional devices that connect to the tablet computing device or smartphone through which a user might interact. In one embodiment, I/O controller 1140 manages devices such as accelerometers, cameras, light sensors or other environmental sensors, or other hardware that can be included in the tablet computing device or smartphone. The input can be part of direct user interaction, as well as providing environmental input to the tablet computing device or smartphone.

In one embodiment, the tablet computing device or smartphone includes power management 1150 that manages battery power usage, charging of the battery, and features related to power saving operation. Memory subsystem 1160 includes memory devices for storing information in the tablet computing device or smartphone. Connectivity 1170 includes hardware devices (e.g., wireless and/or wired connectors and communication hardware) and software components (e.g., drivers, protocol stacks) to the tablet computing device or smartphone to communicate with external devices. Cellular connectivity 1172 may include, for example, wireless carriers such as GSM (global system for mobile communications), CDMA (code division multiple access), TDM (time division multiplexing), or other cellular service standards). Wireless connectivity 1174 may include, for example, activity that is not cellular, such as personal area networks (e.g., Bluetooth), local area networks (e.g., WiFi), and/or wide area networks (e.g., WiMax), or other wireless communication.

Peripheral connections 1180 include hardware interfaces and connectors, as well as software components (e.g., drivers, protocol stacks) to make peripheral connections as a peripheral device (“to” 1182) to other computing devices, as well as have peripheral devices (“from” 1184) connected to the tablet computing device or smartphone, including, for example, a “docking” connector to connect with other computing devices. Peripheral connections 1180 include common or standards-based connectors, such as a Universal Serial Bus (USB) connector, DisplayPort including MiniDisplayPort (MDP), High Definition Multimedia Interface (HDMI), Firewire, etc.

FIG. 12 illustrates a diagrammatic representation of a machine in the example form of a computing system 1200 within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine may be connected (e.g., networked) to other machines in a LAN, an intranet, an extranet, or the Internet. The machine may operate in the capacity of a server or a client device in a client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a server, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

The computing system 1200 includes a processing device 1202, a main memory 1204 (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) (such as synchronous DRAM (SDRAM) or DRAM (RDRAM), etc.), a static memory 1206 (e.g., flash memory, static random access memory (SRAM), etc.), and a data storage device 1218, which communicate with each other via a bus 1230.

Processing device 1202 represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. More particularly, the processing device may be complex instruction set computing (CISC) microprocessor, reduced instruction set computer (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or processor implementing other instruction sets, or processors implementing a combination of instruction sets. Processing device 1202 may also be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. In one embodiment, processing device 1202 may include one or processing cores. The processing device 1202 is configured to execute the processing logic 1226 for performing the operations discussed herein. In one embodiment, processing device 1202 is the same as computer systems 100 and 200 as described with respect to FIG. 1 that implements the NPEBS module 106. Alternatively, the computing system 1200 can include other components as described herein.

The computing system 1200 may further include a network interface device 1208 communicably coupled to a network 1220. The computing system 1200 also may include a video display unit 1210 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)), an alphanumeric input device 1212 (e.g., a keyboard), a cursor control device 1214 (e.g., a mouse), a signal generation device 1216 (e.g., a speaker), or other peripheral devices. Furthermore, computing system 1200 may include a graphics processing unit 1222, a video processing unit 1228 and an audio processing unit 1232. In another embodiment, the computing system 1200 may include a chipset (not illustrated), which refers to a group of integrated circuits, or chips, that are designed to work with the processing device 1202 and controls communications between the processing device 1202 and external devices. For example, the chipset may be a set of chips on a motherboard that links the processing device 1202 to very high-speed devices, such as main memory 1204 and graphic controllers, as well as linking the processing device 1202 to lower-speed peripheral buses of peripherals, such as USB, PCI or ISA buses.

The data storage device 1218 may include a computer-readable storage medium 1224 on which is stored software 1226 embodying any one or more of the methodologies of functions described herein. The software 1226 may also reside, completely or at least partially, within the main memory 1204 as instructions 1226 and/or within the processing device 1202 as processing logic 1226 during execution thereof by the computing system 1200; the main memory 1204 and the processing device 1202 also constituting computer-readable storage media.

The computer-readable storage medium 1224 may also be used to store instructions 1226 utilizing the NPEBS module 106 described with respect to FIG. 1 and/or a software library containing methods that call the above applications. While the computer-readable storage medium 1224 is shown in an example embodiment to be a single medium, the term “computer-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instruction for execution by the machine and that cause the machine to perform any one or more of the methodologies of the embodiments. The term “computer-readable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media. While the invention has been described with respect to a limited number of embodiments, those skilled in the art will appreciate numerous modifications and variations therefrom. It is intended that the appended claims cover all such modifications and variations as fall within the true spirit and scope of this invention.

The following examples pertain to further embodiments.

Example 1 is a processing device comprising a plurality of clusters, wherein each of the plurality of clusters comprises a plurality of cores and a plurality of cache slices co-located within the plurality of cores and a virtual shared cache comprising the plurality of clusters wherein cache data in the plurality of cache slices is shared among the plurality of clusters.

In Example 2, the subject matter of Example 1 can optionally include wherein the core pushes the cache data from a cluster among the plurality of clusters to another cluster among the plurality of clusters.

In Example 3, the subject matter of any one of Examples 1-2 can optionally include wherein the cache data is pushed into the another cluster based on an address within an address range allocated to the cache slice in the cluster among the plurality of clusters.

In Example 4, the subject matter of any one of Examples 1-3 can optionally include wherein the cache data is pushed based on availability of capacity of cache memory in the cluster among the plurality of clusters.

In Example 5, the subject matter of any one of Examples 1-4 can optionally include wherein the cache data is pushed based on the core among the plurality of cores executing a thread.

In Example 6, the subject matter of any one of Examples 1-5 can optionally include wherein the core searches for the cache data in parallel within a cluster among the plurality of clusters and in the virtual shard cache.

In Example 7, the subject matter of any one of Examples 1-6 can optionally include wherein the cache data is retrieved from one of the cluster among the plurality of clusters or the virtual shared cache.

Example 8 is a system comprising a memory and a processing device communicably coupled to the memory, wherein the processing device comprises a plurality of clusters, wherein each of the plurality of clusters comprises a plurality of cores and a plurality of cache slices co-located within the plurality of cores and a virtual shared cache comprising the plurality of clusters wherein cache data in the plurality of cache slices is shared among the plurality of clusters.

In Example 9, the subject matter of Example 8 can optionally include wherein the core pushes the cache data from a cluster among the plurality of clusters is pushed to another cluster among the plurality of clusters.

In Example 10, the subject matter of any one of Examples 8-9, can optionally include wherein the core searches for the cache data in parallel within a cluster among the plurality of clusters and from the virtual shared cache.

Example 11 is a method comprising allocating a plurality of clusters into a virtual shared cache, wherein each of the clusters comprise a plurality of cores and a plurality of cache slices co-located within the plurality of cores and sharing a cache data in the plurality of cache slices among the plurality of clusters.

In Example 12, the subject matter of Example 11 can optionally include wherein the sharing further comprising pushing the cache data from a cluster among the plurality of clusters to another cluster among the plurality of clusters.

In Example 13, the subject matter of any one of Examples 11-12 can optionally include wherein the cache data is pushed into the another cluster based on an address within an address range allocated to the cache slice in the cluster among the plurality of clusters.

In Example 14, the subject matter of any one of Examples 11-13 can optionally include wherein the cache data is pushed based on availability of capacity of cache memory in the cluster among the plurality of clusters.

In Example 15, the subject matter of any one of Examples 11-14 can optionally include wherein the sharing further comprising searching in parallel for the cache data within a cluster among the plurality of clusters and in the virtual shared cache and retrieving the cache data from one of the cluster among the plurality of clusters or the virtual shared cache.

Example 16 is a non-transitory machine-readable storage medium including data that, when accessed by a processing device, cause the processing device to perform operations comprising allocating a plurality of clusters into a virtual shared cache, wherein each of the clusters comprise a plurality of cores and a plurality of cache slices co-located within the plurality of cores and sharing a cache data in the plurality of cache slices among the plurality of clusters.

In Example 17, the subject matter of Example 16 can optionally include wherein the sharing further comprising pushing the cache data from a cluster among the plurality of clusters to another cluster among the plurality of clusters.

In Example 18, the subject matter of any one of Examples 16-17 can optionally include wherein the cache data is pushed based an address within an address range allocated to the cache slice in the cluster among the plurality of clusters.

In Example 19, the subject matter of any one of Examples 17-18 an optional include wherein the cache data is pushed based on one of availability of capacity of cache memory in the cluster among the plurality of clusters or the core among the plurality of cores executing a thread.

In Example 20, the subject matter of any one of Examples 17-19 can optionally include wherein the sharing further comprising searching in parallel for the cache data within a cluster among the plurality of clusters and in the virtual shared cache and retrieving the cache data from one of the cluster among the plurality of clusters or the virtual shared cache.

Various embodiments may have different combinations of the structural features described above. For instance, all optional features of the SOC described above may also be implemented with respect to a processor described herein and specifics in the examples may be used anywhere in one or more embodiments.

A design may go through various stages, from creation to simulation to fabrication. Data representing a design may represent the design in a number of manners. First, as is useful in simulations, the hardware may be represented using a hardware description language or another functional description language. Additionally, a circuit level model with logic and/or transistor gates may be produced at some stages of the design process. Furthermore, most designs, at some stage, reach a level of data representing the physical placement of various devices in the hardware model. In the case where conventional semiconductor fabrication techniques are used, the data representing the hardware model may be the data specifying the presence or absence of various features on different mask layers for masks used to produce the integrated circuit. In any representation of the design, the data may be stored in any form of a machine readable medium. A memory or a magnetic or optical storage such as a disc may be the machine readable medium to store information transmitted via optical or electrical wave modulated or otherwise generated to transmit such information. When an electrical carrier wave indicating or carrying the code or design is transmitted, to the extent that copying, buffering, or re-transmission of the electrical signal is performed, a new copy is made. Thus, a communication provider or a network provider may store on a tangible, machine-readable medium, at least temporarily, an article, such as information encoded into a carrier wave, embodying techniques of embodiments of the present disclosure.

A module as used herein refers to any combination of hardware, software, and/or firmware. As an example, a module includes hardware, such as a micro-controller, associated with a non-transitory medium to store code adapted to be executed by the micro-controller. Therefore, reference to a module, in one embodiment, refers to the hardware, which is specifically configured to recognize and/or execute the code to be held on a non-transitory medium. Furthermore, in another embodiment, use of a module refers to the non-transitory medium including the code, which is specifically adapted to be executed by the microcontroller to perform predetermined operations. And as can be inferred, in yet another embodiment, the term module (in this example) may refer to the combination of the microcontroller and the non-transitory medium. Often module boundaries that are illustrated as separate commonly vary and potentially overlap. For example, a first and a second module may share hardware, software, firmware, or a combination thereof, while potentially retaining some independent hardware, software, or firmware. In one embodiment, use of the term logic includes hardware, such as transistors, registers, or other hardware, such as programmable logic devices.

Use of the phrase ‘configured to,’ in one embodiment, refers to arranging, putting together, manufacturing, offering to sell, importing and/or designing an apparatus, hardware, logic, or element to perform a designated or determined task. In this example, an apparatus or element thereof that is not operating is still ‘configured to’ perform a designated task if it is designed, coupled, and/or interconnected to perform said designated task. As a purely illustrative example, a logic gate may provide a 0 or a 1 during operation. But a logic gate ‘configured to’ provide an enable signal to a clock does not include every potential logic gate that may provide a 1 or 0. Instead, the logic gate is one coupled in some manner that during operation the 1 or 0 output is to enable the clock. Note once again that use of the term ‘configured to’ does not require operation, but instead focus on the latent state of an apparatus, hardware, and/or element, where in the latent state the apparatus, hardware, and/or element is designed to perform a particular task when the apparatus, hardware, and/or element is operating.

Furthermore, use of the phrases ‘to,’ ‘capable of/to,’ and or ‘operable to,’ in one embodiment, refers to some apparatus, logic, hardware, and/or element designed in such a way to enable use of the apparatus, logic, hardware, and/or element in a specified manner. Note as above that use of to, capable to, or operable to, in one embodiment, refers to the latent state of an apparatus, logic, hardware, and/or element, where the apparatus, logic, hardware, and/or element is not operating but is designed in such a manner to enable use of an apparatus in a specified manner.

A value, as used herein, includes any known representation of a number, a state, a logical state, or a binary logical state. Often, the use of logic levels, logic values, or logical values is also referred to as 1's and 0's, which simply represents binary logic states. For example, a 1 refers to a high logic level and 0 refers to a low logic level. In one embodiment, a storage cell, such as a transistor or flash cell, may be capable of holding a single logical value or multiple logical values. However, other representations of values in computer systems have been used. For example the decimal number ten may also be represented as a binary value of 910 and a hexadecimal letter A. Therefore, a value includes any representation of information capable of being held in a computer system.

Moreover, states may be represented by values or portions of values. As an example, a first value, such as a logical one, may represent a default or initial state, while a second value, such as a logical zero, may represent a non-default state. In addition, the terms reset and set, in one embodiment, refer to a default and an updated value or state, respectively. For example, a default value potentially includes a high logical value, i.e. reset, while an updated value potentially includes a low logical value, i.e. set. Note that any combination of values may be utilized to represent any number of states.

The embodiments of methods, hardware, software, firmware or code set forth above may be implemented via instructions or code stored on a machine-accessible, machine readable, computer accessible, or computer readable medium which are executable by a processing element. A non-transitory machine-accessible/readable medium includes any mechanism that provides (i.e., stores and/or transmits) information in a form readable by a machine, such as a computer or electronic system. For example, a non-transitory machine-accessible medium includes random-access memory (RAM), such as static RAM (SRAM) or dynamic RAM (DRAM); ROM; magnetic or optical storage medium; flash memory devices; electrical storage devices; optical storage devices; acoustical storage devices; other form of storage devices for holding information received from transitory (propagated) signals (e.g., carrier waves, infrared signals, digital signals); etc., which are to be distinguished from the non-transitory mediums that may receive information there from.

Instructions used to program logic to perform embodiments of the disclosure may be stored within a memory in the system, such as DRAM, cache, flash memory, or other storage. Furthermore, the instructions can be distributed via a network or by way of other computer readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), but is not limited to, floppy diskettes, optical disks, Compact Disc, Read-Only Memory (CD-ROMs), and magneto-optical disks, Read-Only Memory (ROMs), Random Access Memory (RAM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), magnetic or optical cards, flash memory, or a tangible, machine-readable storage used in the transmission of information over the Internet via electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Accordingly, the computer-readable medium includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).

Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

In the foregoing specification, a detailed description has been given with reference to specific exemplary embodiments. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the disclosure as set forth in the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative sense rather than a restrictive sense. Furthermore, the foregoing use of embodiment and other exemplarily language does not necessarily refer to the same embodiment or the same example, but may refer to different and distinct embodiments, as well as potentially the same embodiment. 

What is claimed is:
 1. A processing device, comprising: a plurality of sub-non-uniform memory access (sub-NUMA) clusters each comprising a plurality of cores, wherein each core of the plurality of cores comprising a plurality of cache slices co-located within the core; and a virtual shared cache comprising the plurality of sub-NUMA clusters, wherein cache capacity of the plurality of cache slices is shared among the plurality of sub-NUMA clusters.
 2. The processing device of claim 1, wherein a core among the plurality of cores pushes cache data from a first cluster among the plurality of sub-NUMA clusters to a second cluster among the plurality of sub-NUMA clusters.
 3. The processing device of claim 2, wherein the cache data is pushed into the second cluster based on an address within an address range allocated to the cache slice in the first cluster.
 4. The processing device of claim 2, wherein the cache data is pushed based on availability of the cache capacity in at least one of the first cluster or the second cluster.
 5. The processing device of claim 2, wherein the cache data is pushed based on proximity to a core among the plurality of cores executing a thread that is utilizing the cache data.
 6. The processing device of claim 1, wherein a core among the plurality of cores searches for cache data in parallel within: a first sub-NUMA cluster among the plurality of sub-NUMA clusters, wherein the first sub-NUMA cluster comprises the core that searches for the cache data; and other sub-NUMA clusters in the virtual shared cache.
 7. The processing device of claim 6, wherein the cache data is retrieved from one of the first sub-NUMA cluster among the plurality of sub-NUMA clusters or the other sub-NUMA clusters in the virtual shared cache.
 8. A system comprising: a memory; and a processing device communicably coupled to the memory, wherein the processing device comprises: a plurality of sub-non-uniform memory access (sub-NUMA) clusters each comprising a plurality of cores, wherein each core of the plurality of cores comprising a plurality of cache slices co-located within the core; and a virtual shared cache comprising the plurality of sub-NUMA clusters, wherein cache capacity of the plurality of cache slices is shared among the plurality of sub-NUMA clusters.
 9. The system of claim 8, wherein the core among the plurality of cores pushes cache data from a first cluster among the plurality of sub-NUMA clusters to a second cluster among the plurality of sub-NUMA clusters.
 10. The system of claim 8, wherein a core searches for cache data in parallel within: a first sub-NUMA cluster among the plurality of sub-NUMA clusters, wherein the first sub-NUMA cluster comprises the core that searches for the cache data; and other sub-NUMA clusters in the virtual shared cache.
 11. A method comprising: allocating a plurality of sub-non-uniform memory access (sub-NUMA) clusters into a virtual shared cache, wherein each of the sub-NUMA clusters comprise a plurality of cores, each core of the plurality of cores comprising a plurality of cache slices co-located within the core; and sharing a cache capacity of the plurality of cache slices among the plurality of sub-NUMA clusters of the virtual shared cache.
 12. The method of claim 11, wherein the sharing further comprising pushing cache data from a first cluster among the plurality of sub-NUMA clusters to a second cluster among the plurality of sub-NUMA clusters.
 13. The method of claim 12, wherein the cache data is pushed into the second cluster based on an address within an address range allocated to the cache slice in the first cluster.
 14. The method of claim 12, wherein the cache data is pushed based on availability of the cache capacity in at least one of the first cluster or the second cluster.
 15. The method of claim 11, wherein the sharing further comprising: searching in parallel for cache data within: a first sub-NUMA cluster among the plurality of sub-NUMA clusters, wherein the first sub-NUMA cluster comprises the core that searches for the cache data; and other sub-NUMA clusters in the virtual shared cache; and retrieving the cache data from one of the first sub-NUMA cluster among the plurality of sub-NUMA clusters or the virtual shared cache.
 16. A non-transitory machine-readable storage medium including data that, when accessed by a processing device, cause the processing device to perform operations comprising: allocating a plurality of sub-non-uniform memory access (sub-NUMA) clusters into a virtual shared cache, wherein each of the sub-NUMA clusters comprise a plurality of cores, each core of the plurality of cores comprising a plurality of cache slices co-located within the core; and sharing a cache capacity of the plurality of cache slices among the plurality of sub-NUMA clusters of the virtual shared cache.
 17. The non-transitory machine-readable storage medium of claim 16, wherein the sharing further comprising pushing cache data from a first cluster among the plurality of sub-NUMA clusters to a second cluster among the plurality of sub-NUMA clusters.
 18. The non-transitory machine-readable storage medium of claim 17, wherein the cache data is pushed into the second cluster based on an address within an address range allocated to the cache slice in the first cluster.
 19. The non-transitory machine-readable storage medium of claim 17, wherein the cache data is pushed based on at least one of: availability of the cache capacity in at least one of the first cluster or the second cluster; proximity to the core among the plurality of cores executing a thread that is utilizing the cache data.
 20. The non-transitory machine-readable storage medium of claim 16, wherein the sharing further comprising: searching in parallel for cache data within: a first sub-NUMA cluster among the plurality of sub-NUMA clusters, wherein the first sub-NUMA cluster comprises the core that searches for the cache data; and other sub-NUMA clusters in the virtual shared cache; and retrieving the cache data from one of the first sub-NUMA cluster among the plurality of sub-NUMA clusters or the virtual shared cache. 